Datalicious Depths of Delectable Data

Want to jump to a specific question?

Which results are the most common?

See, if Open Psychometrics recorded the respondents’ results, it would be quite quick to answer this question. Unfortunately, they didn’t, and we’re working with a bunch of numbers!

This is what the data looks like:

I’ve selected the first 6 columns.. and it’s not too bad! It’s a little intimidating to think that there are over 1 million more rows, but we’ve gotta start somewhere >:)

We start by calculating the scores for the ‘Extroversion’ personality trait. We can do this by summing up the scores of the 10 EXT (standing for EXTroversion) questions. However, it should be noted that answering a ‘4’ or ‘5’ on a EXT question doesn’t always mean that a user is more extroverted. For example, answering 5 for “I don’t talk a lot” vs “I am the life of the party” would significantly affect your results.

So, we’ll need to make sure to add and subtract scores as necessary, depending on how the questions are keyed. I’ve arbitrarily made the decision to ‘positively key’ questions symbolising extroversion (meaning that I’d add points to their total score if they showed signs of extroversion), and ‘negatively key’ questions symbolising introversion (subtracting points from total score). See the table below to better understand this keying:

Table 1: EXT Question Key
Questions Key
I am the life of the party. \(+\)
I don’t talk a lot. \(-\)
I feel comfortable around people. \(+\)
I keep in the background. \(-\)
I start conversations. \(+\)
I have little to say. \(-\)
I talk to a lot of different people at parties. \(+\)
I don’t like to draw attention to myself. \(-\)
I don’t mind being the center of attention. \(+\)
I am quiet around strangers. \(-\)

Hence, after adding/subtracting their points from each question, any positive total score (> 0) will mean that the user receives an ‘S’ for Sociable, while a negative score (< 0) would result in an ‘R’.1 If their score is 0, then they’d receive an ‘X’, as their results since they’re perfectly in-between, and will remain inconclusive.

Below is a sample table of results, where extletter (their final letter result) and extscore (the sum of their points) are calculated from the raw data.


We can also visualize our results into a graph:

The same processes will be applied to the other personality traits, with their graphs located below:

Now, we can combine everybody’s letters from each personality traits to form their final result, then determine which results are the most common within this data set.

In fact, we can see the 25 most common results below:


WOOO! Congratulations to the XXOAI family for being among the most common result out of 243 possibilities!

If you’d prefer to see a more numerical representation, I’ve provided a table with the exact number of each result and the average score of each personality trait2:

Table 2: The 10 Most Common Results
Results Amount of Responses Percentage of People
SCOAI 159575 15.716379
RLOAI 121251 11.941888
SLOAI 100841 9.931727
RCOAI 92548 9.114958
RLUAI 70642 6.957459
SLUAI 56870 5.601068
SCUAI 41138 4.051640
RCUAI 26379 2.598041
RLOEI 23547 2.319120
RCOEI 22333 2.199554
Table 3: Average Score for Each Personliaty Trait
Extroversion Neuroticism Conscientiousness Agreeableness Openness
avgscore -2.533333 -2 3.546667 6.84 9.013333

Let’s try to analyze why these results happened.

Extrovertism

Extrovertism is the most balanced trait, as there seems to be a nice mix of S(ocial) and R(eserved) – representative of the larger population. I’d assume this is because questions in this trait were very straight-forward (e.g. “I start conversations”), and users likely display/are conscious of these behaviors in their everyday life. Hence, with a more ‘objective’ viewpoint, this removes the issue of self-bias and leads to more accurate results.

There are also about ~40k more introverts compared to extroverts. Maybe the S’s aren’t as likely to spend 20 minutes on an online test, compared to R’s?

Neuroticism

Once again, a solid distribution of results between C(alm) and L(imbic), mirroring what I’d expect the general population to be like. Similar to the extrovertism section, the questions tend to be straightforward and there’s relatively less self-bias within the trait, as many people are conscious of their emotions, and whether or not they control them.

There are ~60000 more limbic people compared to calm. I’m not really surprised - people are more stressed3 and more sad4 than we’ve ever been. Furthermore, emotional regulation is a result of introspection and reflection. As our society slowly moves towards constant stimulation and excess, it’s no wonder we struggle to achieve emotional stability.

Conscientiousness, Agreeableness, and Openness

With these three traits, we start to see a much larger gap between the possible letters. There are significantly more people that are organized, agreeable, and inquisitive, relative to unstructured, egocentric, and non-inquisitive.

I definitely don’t think these results reflect the general population, despite the fact that I have no evidence stating so. If I had to speculate, I’d say that this data is just a tiny bit biased, leading to skewed results.

  1. We’re just a little bit tainted

No matter how hard we try, we can never be completely objective. Many struggle to see things beyond ourselves, to judge every action we take from a neutral standpoint.

In normal, everyday life, this is not too significant of an issue. A little bit of subjectivity never hurt anybody! However, when we’re trying to objectively analyze and record data about ourselves, since this is a self-administered quiz, our lack of objectivity can lead to delusional answers.

  1. We’re fragile creatures

For these three categories, there are clear ‘winners’. In this society, it is almost ALWAYS better if you’re organized, agreeable, and inquisitive, rather than the opposite. In fact, it’s almost an insult if we AREN’T these things, because that means we should ‘be better’.5 For example, you may want to be agreeable and people-pleasing, since it shows that you’re friendly and nice, and people will tend to ‘like’ you more, instead of if you’re confrontational and assertive for your own needs. Or, as our society moves towards maximizing productivity and ‘grind culture’, you NEED to be conscientious and self-disciplined, or else you won’t be successful. Or, people don’t want to be seen as rigid and unwilling to try new things. Society will call them scaredy-cats, boring, or that you’re ‘bringing the mood down’.

It doesn’t help that we don’t like being ‘bad people’ – we constantly attempt to justify our actions to be good and perceive ourselves in a positive light. We are rarely the villains in our own stories; it’s always the other person doing something wrong, or doing something worse than we did, or they started the ordeal.

However, when we can’t be objective, we can confuse what we actually do, to what we wish we did. This is going to lead us to choose answers corresponding to those ‘better’ traits of self-discipline, agreeableness and inquisitiveness, instead of objectively saying we have the ‘worse’ traits of unstructuredness, egocentrism and un-inquisitiveness.

  1. We’re just built for this (for Openness)

There’s also the classic case of sampling bias. The people who take this quiz are probably curious about psychology, want to know more about themselves, and are willing to try something new. These are typically the types of people who are inquisitive (matching with the I letter) instead of non-inquisitive (matching with the N letter).

Sheer Statistical Impossibility…?

However, When analyzing this data, it seems.. strange that so many __OAI types are represented. In fact, it feels weird that 15%(!!!!) of people were the EXACT SAME TYPE, despite ALL POSSIBLE COMBINATIONS!

So, let’s see how it compares to the theoretical data. Using the data6 from SimilarMinds, we can see how our data stacks up.

Table 4: Theoretical Data
Results Percentage of People
SCOAI 3.4
RLOAI 2.7
SLOAI 2.5
RCOAI 3.5
RLUAI N/A
SLUAI 3.4
SCUAI 4.1
RCUAI N/A
RLOEI N/A
RCOEI N/A
Table 4: Experimental Data
Results Percentage of People
SCOAI 15.716379
RLOAI 11.941888
SLOAI 9.931727
RCOAI 9.114958
RLUAI 6.957459
SLUAI 5.601068
SCUAI 4.051640
RCUAI 2.598041
RLOEI 2.319120
RCOEI 2.199554

Looking at these tables, there’s a clear discrepancy between theoretical and experimental data, where none of the theoretical results really match up to what is seen in our data set – certain results are far more represented than the average value.

However, most of it can be explained by the previous analysis: Wrong results might occur because of biases and societal norms (cementing the last two letters to be A and I), in addition to the natural disposition of respondents.

Honestly, I’m not too sure why 15% of people are SCOAI, maybe people are being influenced to answer what they WANT to be like, rather than what they actually are, since SCOAI seems like one of the most ‘socially-successful’ results.7 So, in reality, I think that many respondents are not actually SCOAIs. That’s my best guess!8

Also, just to provide a comphrensive review of the results, here’s a list of the most uncommon ones!

Table 5: Most Uncommon Results
Results Amount of Responses
XXUXN 3
SXXXN 5
XLXXN 5
XXUEX 5
SCXXX 6
XCXEX 6
XXOXN 7
SXOXX 9
XCUXX 9
XCXXN 9

No surprise, it’s a lot of results with X’s!

At first, I was surprised that ‘XXXXX’ didn’t appear, since I’d assume it (theoretically) is the most unlikely.9 However, I wouldn’t be surprised if only 5% of respondents were genuinely XXXXX, while the other 95% of people who got the result just kept clicking 3 (Neutral) for every question, or had some kind of game to see if they could get the (theoretically) super rare XXXXX.

Do results vary between countries?

This data contains 224 unique ISO country codes10. Let’s dig through this data - a fun bit of stalking!

We can see that the majority of data came from the US, with a whopping total of 546403 respondents. Trailing (very far) behind, we also have Great Britain (GB), Canada (CA), and Australia (AU).

This is likely because this quiz is in English, and will generally cater towards countries with English as their primary language. In addition, Google’s SEO (Search Engine Optimization) is also affected by location, and can rank websites by their proximity to the user.11 So, it’s possible that Open Psychometrics is American12, and when Americans search up “Big Five Personality Test”, this would be the first quiz that shows up.13

But, we’re not really concerned on WHERE people are taking the quiz. Instead, we only care about how it affects the responses. Hence, we’re going to start by finding the most common results for America, Great Britain, Australia, and the Philippians –these location shave the most amount of results while being from different continents– and seeing how they compare to one another.

Table 6: America
Results Percentage
SCOAI 16.855325
RLOAI 12.283425
SLOAI 10.141050
RCOAI 9.943943
RLUAI 6.578112
SLUAI 5.344041
SCUAI 4.044268
RCUAI 2.546472
RCOEI 2.150610
RLOEI 2.142924
Table 6: Great Britian
Results Percentage
SCOAI 13.129918
RLOAI 11.623821
SLOAI 10.149258
RLUAI 8.353355
SLUAI 7.272208
RCOAI 6.776683
SCUAI 4.606883
RLOEI 2.660820
RCUAI 2.575230
RLUEI 2.386029
Table 6: Australia
Results Percentage
SCOAI 16.546072
RLOAI 11.279233
SLOAI 9.696182
RCOAI 9.020588
RLUAI 6.534080
SLUAI 5.954427
SCUAI 4.309414
RCUAI 2.372577
RLOEI 2.072756
RCOEI 2.046772
Table 6: Philippines
Results Percentage
RLOAI 15.105557
SCOAI 11.699501
SLOAI 10.540636
RCOAI 8.726760
RLUAI 5.869905
SLUAI 3.305285
RLOEI 2.216960
RLOAN 2.191767
XLOAI 1.889454
RCUAI 1.627450

From the above table, it’s pretty clear that countries have very similar trends, with the top 7 result virtually the same between all countries. However, there are slight differences you can take out of it:

Let’s try zooming out by plotting the averages on a world map, and then analyzing results.

A note on the data: Locations with less than 10 responses have been omitted from the data, as they often significantly skewed maps. This removed 58 locations off the map, with Africa losing a pretty big chunk of their land.

(#fig:extscores world map)Diamond sadasds

Higher scores are correlated with extroversion, lower scores are correlated introversion.

Table 7: Most Extroverted
region ExtScores
Cuba 2.708333
Greenland 2.382353
Rwanda 2.093750
Ethiopia 1.342960
Afghanistan 1.018519
Norway 0.989608
Table 7: Least Extroverted
region ExtScores
St. Kitts & Nevis -6.333333
Sudan -5.466667
St. Lucia -5.190476
Åland Islands -4.733333
Guyana -4.543478
Bhutan -4.500000

There doesn’t seem to be a clear trend in the world, but there seems to be several generalizations.

It’s quite interesting that the sterotype is that Americans are more extroverted, while Asians are more introverted. Doesn’t seem to apply to this dataset!

    Longitude Latitude group order      region subregion estScores
1   -69.89912 12.45200     1     1       Aruba      <NA> 0.6470588
2   -69.89571 12.42300     1     2       Aruba      <NA> 0.6470588
3   -69.94219 12.43853     1     3       Aruba      <NA> 0.6470588
4   -70.00415 12.50049     1     4       Aruba      <NA> 0.6470588
5   -70.06612 12.54697     1     5       Aruba      <NA> 0.6470588
6   -70.05088 12.59707     1     6       Aruba      <NA> 0.6470588
7   -70.03511 12.61411     1     7       Aruba      <NA> 0.6470588
8   -69.97314 12.56763     1     8       Aruba      <NA> 0.6470588
9   -69.91181 12.48047     1     9       Aruba      <NA> 0.6470588
10  -69.89912 12.45200     1    10       Aruba      <NA> 0.6470588
11   74.89131 37.23164     2    12 Afghanistan      <NA> 1.7407407
12   74.84023 37.22505     2    13 Afghanistan      <NA> 1.7407407
13   74.76738 37.24917     2    14 Afghanistan      <NA> 1.7407407
14   74.73896 37.28564     2    15 Afghanistan      <NA> 1.7407407
15   74.72666 37.29072     2    16 Afghanistan      <NA> 1.7407407
16   74.66895 37.26670     2    17 Afghanistan      <NA> 1.7407407
17   74.55899 37.23662     2    18 Afghanistan      <NA> 1.7407407
18   74.37217 37.15771     2    19 Afghanistan      <NA> 1.7407407
19   74.37617 37.13735     2    20 Afghanistan      <NA> 1.7407407
20   74.49796 37.05722     2    21 Afghanistan      <NA> 1.7407407
21   74.52646 37.03066     2    22 Afghanistan      <NA> 1.7407407
22   74.54140 37.02217     2    23 Afghanistan      <NA> 1.7407407
23   74.43106 36.98369     2    24 Afghanistan      <NA> 1.7407407
24   74.19473 36.89688     2    25 Afghanistan      <NA> 1.7407407
25   74.03887 36.82573     2    26 Afghanistan      <NA> 1.7407407
26   74.00185 36.82310     2    27 Afghanistan      <NA> 1.7407407
27   73.90781 36.85293     2    28 Afghanistan      <NA> 1.7407407
28   73.76914 36.88848     2    29 Afghanistan      <NA> 1.7407407
29   73.73183 36.88779     2    30 Afghanistan      <NA> 1.7407407
30   73.41113 36.88169     2    31 Afghanistan      <NA> 1.7407407
31   73.11680 36.86856     2    32 Afghanistan      <NA> 1.7407407
32   72.99374 36.85161     2    33 Afghanistan      <NA> 1.7407407
33   72.76621 36.83501     2    34 Afghanistan      <NA> 1.7407407
34   72.62286 36.82959     2    35 Afghanistan      <NA> 1.7407407
35   72.53135 36.80200     2    36 Afghanistan      <NA> 1.7407407
36   72.43115 36.76582     2    37 Afghanistan      <NA> 1.7407407
37   72.32696 36.74239     2    38 Afghanistan      <NA> 1.7407407
38   72.24980 36.73472     2    39 Afghanistan      <NA> 1.7407407
39   72.15674 36.70088     2    40 Afghanistan      <NA> 1.7407407
40   72.09560 36.63374     2    41 Afghanistan      <NA> 1.7407407
41   71.92070 36.53418     2    42 Afghanistan      <NA> 1.7407407
42   71.82227 36.48608     2    43 Afghanistan      <NA> 1.7407407
43   71.77266 36.43184     2    44 Afghanistan      <NA> 1.7407407
44   71.71641 36.42656     2    45 Afghanistan      <NA> 1.7407407
45   71.62051 36.43647     2    46 Afghanistan      <NA> 1.7407407
46   71.54590 36.37769     2    47 Afghanistan      <NA> 1.7407407
47   71.46328 36.29326     2    48 Afghanistan      <NA> 1.7407407
48   71.31260 36.17119     2    49 Afghanistan      <NA> 1.7407407
49   71.23291 36.12178     2    50 Afghanistan      <NA> 1.7407407
50   71.18506 36.04209     2    51 Afghanistan      <NA> 1.7407407
51   71.22021 36.00068     2    52 Afghanistan      <NA> 1.7407407
52   71.34287 35.93853     2    53 Afghanistan      <NA> 1.7407407
53   71.39756 35.88018     2    54 Afghanistan      <NA> 1.7407407
54   71.42754 35.83374     2    55 Afghanistan      <NA> 1.7407407
55   71.48359 35.71460     2    56 Afghanistan      <NA> 1.7407407
56   71.51904 35.59751     2    57 Afghanistan      <NA> 1.7407407
57   71.57198 35.54683     2    58 Afghanistan      <NA> 1.7407407
58   71.58740 35.46084     2    59 Afghanistan      <NA> 1.7407407
59   71.60059 35.40791     2    60 Afghanistan      <NA> 1.7407407
60   71.57198 35.37041     2    61 Afghanistan      <NA> 1.7407407
61   71.54551 35.32851     2    62 Afghanistan      <NA> 1.7407407
62   71.54551 35.28886     2    63 Afghanistan      <NA> 1.7407407
63   71.57725 35.24800     2    64 Afghanistan      <NA> 1.7407407
64   71.60527 35.21177     2    65 Afghanistan      <NA> 1.7407407
65   71.62051 35.18301     2    66 Afghanistan      <NA> 1.7407407
66   71.60166 35.15068     2    67 Afghanistan      <NA> 1.7407407
67   71.54551 35.10141     2    68 Afghanistan      <NA> 1.7407407
68   71.51709 35.05112     2    69 Afghanistan      <NA> 1.7407407
69   71.45508 34.96694     2    70 Afghanistan      <NA> 1.7407407
70   71.35811 34.90962     2    71 Afghanistan      <NA> 1.7407407
71   71.29414 34.86773     2    72 Afghanistan      <NA> 1.7407407
72   71.22578 34.77954     2    73 Afghanistan      <NA> 1.7407407
73   71.11328 34.68159     2    74 Afghanistan      <NA> 1.7407407
74   71.06563 34.59961     2    75 Afghanistan      <NA> 1.7407407
75   71.01631 34.55464     2    76 Afghanistan      <NA> 1.7407407
76   70.96562 34.53037     2    77 Afghanistan      <NA> 1.7407407
77   70.97891 34.48628     2    78 Afghanistan      <NA> 1.7407407
78   71.02295 34.43115     2    79 Afghanistan      <NA> 1.7407407
79   71.09570 34.36943     2    80 Afghanistan      <NA> 1.7407407
80   71.09238 34.27324     2    81 Afghanistan      <NA> 1.7407407
81   71.08906 34.20406     2    82 Afghanistan      <NA> 1.7407407
82   71.09131 34.12027     2    83 Afghanistan      <NA> 1.7407407
83   71.05156 34.04971     2    84 Afghanistan      <NA> 1.7407407
84   70.84844 33.98188     2    85 Afghanistan      <NA> 1.7407407
85   70.65401 33.95229     2    86 Afghanistan      <NA> 1.7407407
86   70.41573 33.95044     2    87 Afghanistan      <NA> 1.7407407
87   70.32568 33.96113     2    88 Afghanistan      <NA> 1.7407407
88   70.25361 33.97598     2    89 Afghanistan      <NA> 1.7407407
89   69.99473 34.05181     2    90 Afghanistan      <NA> 1.7407407
90   69.88965 34.00727     2    91 Afghanistan      <NA> 1.7407407
91   69.86806 33.89766     2    92 Afghanistan      <NA> 1.7407407
92   70.05664 33.71987     2    93 Afghanistan      <NA> 1.7407407
93   70.13418 33.62075     2    94 Afghanistan      <NA> 1.7407407
94   70.21973 33.45469     2    95 Afghanistan      <NA> 1.7407407
95   70.28418 33.36904     2    96 Afghanistan      <NA> 1.7407407
96   70.26113 33.28901     2    97 Afghanistan      <NA> 1.7407407
97   70.09023 33.19810     2    98 Afghanistan      <NA> 1.7407407
98   69.92012 33.11250     2    99 Afghanistan      <NA> 1.7407407
99   69.70371 33.09473     2   100 Afghanistan      <NA> 1.7407407
100  69.56777 33.06416     2   101 Afghanistan      <NA> 1.7407407
101  69.50156 33.02007     2   102 Afghanistan      <NA> 1.7407407
102  69.45312 32.83281     2   103 Afghanistan      <NA> 1.7407407
103  69.40459 32.76426     2   104 Afghanistan      <NA> 1.7407407
104  69.40537 32.68272     2   105 Afghanistan      <NA> 1.7407407
105  69.35947 32.59033     2   106 Afghanistan      <NA> 1.7407407
106  69.28994 32.53057     2   107 Afghanistan      <NA> 1.7407407
107  69.24140 32.43354     2   108 Afghanistan      <NA> 1.7407407
108  69.25654 32.24946     2   109 Afghanistan      <NA> 1.7407407
109  69.27930 31.93682     2   110 Afghanistan      <NA> 1.7407407
110  69.18691 31.83809     2   111 Afghanistan      <NA> 1.7407407
111  69.08311 31.73848     2   112 Afghanistan      <NA> 1.7407407
112  68.97343 31.66738     2   113 Afghanistan      <NA> 1.7407407
113  68.86895 31.63423     2   114 Afghanistan      <NA> 1.7407407
114  68.78233 31.64643     2   115 Afghanistan      <NA> 1.7407407
115  68.71367 31.70806     2   116 Afghanistan      <NA> 1.7407407
116  68.67324 31.75972     2   117 Afghanistan      <NA> 1.7407407
117  68.59766 31.80298     2   118 Afghanistan      <NA> 1.7407407
118  68.52071 31.79414     2   119 Afghanistan      <NA> 1.7407407
119  68.44326 31.75449     2   120 Afghanistan      <NA> 1.7407407
120  68.31982 31.76767     2   121 Afghanistan      <NA> 1.7407407
121  68.21397 31.80737     2   122 Afghanistan      <NA> 1.7407407
122  68.16103 31.80298     2   123 Afghanistan      <NA> 1.7407407
123  68.13017 31.76328     2   124 Afghanistan      <NA> 1.7407407
124  68.01719 31.67798     2   125 Afghanistan      <NA> 1.7407407
125  67.73985 31.54819     2   126 Afghanistan      <NA> 1.7407407
126  67.62675 31.53877     2   127 Afghanistan      <NA> 1.7407407
127  67.57822 31.50649     2   128 Afghanistan      <NA> 1.7407407
128  67.59756 31.45332     2   129 Afghanistan      <NA> 1.7407407
129  67.64706 31.40996     2   130 Afghanistan      <NA> 1.7407407
130  67.73350 31.37925     2   131 Afghanistan      <NA> 1.7407407
131  67.73789 31.34395     2   132 Afghanistan      <NA> 1.7407407
132  67.66152 31.31299     2   133 Afghanistan      <NA> 1.7407407
133  67.59639 31.27769     2   134 Afghanistan      <NA> 1.7407407
134  67.45283 31.23462     2   135 Afghanistan      <NA> 1.7407407
135  67.28730 31.21782     2   136 Afghanistan      <NA> 1.7407407
136  67.11592 31.24292     2   137 Afghanistan      <NA> 1.7407407
137  67.02773 31.30024     2   138 Afghanistan      <NA> 1.7407407
138  66.92432 31.30561     2   139 Afghanistan      <NA> 1.7407407
139  66.82929 31.26367     2   140 Afghanistan      <NA> 1.7407407
140  66.73135 31.19453     2   141 Afghanistan      <NA> 1.7407407
141  66.62422 31.04604     2   142 Afghanistan      <NA> 1.7407407
142  66.59580 31.01997     2   143 Afghanistan      <NA> 1.7407407
 [ reached 'max' / getOption("max.print") -- omitted 82816 rows ]

Higher scores are correlated with being calm, lower scores are correlated being limbic.

Table 8: Most Calm
region estScores
Suriname 4.697674
Eswatini 3.461539
Ethiopia 3.451264
Cape Verde 3.181818
Cuba 3.000000
Papua New Guinea 2.791667
Table 8: Least Calm
region estScores
Jersey -4.476191
Guernsey -4.044444
Syria -3.875000
Samoa -3.727273
Algeria -3.234310
Belize -3.125000

It seems like the south-eastern part of the world is less limbic, specifically Africa and East Asia. I find it funny that China specifically is seen to be relatively ‘calm’, as they are notorious for bad work-life balances14, the ‘lie down’ movement15 – things that show the ‘mentally-difficult’ conditions that they are living it.

Yet, it’s also reasonable to say that Chinese people are accustomed to high stress when dealing with academic pressures.16 Hence, they might have learned to become more emotionally stable.

Higher scores are correlated with organization and contentiousness, lower scores are correlated carelessness.

Table 9: Most Contentious
region csnScores
Ghana 6.922794
Papua New Guinea 6.708333
Grenada 6.291667
Rwanda 6.281250
Uganda 6.127517
Kenya 6.111744
Table 9: Least Contentious
region csnScores
Bhutan -1.0000000
Bolivia 0.0575342
Libya 0.1764706
Angola 0.3571429
Åland Islands 0.6000000
Paraguay 0.6975089

For conscientiousness, Africa is lit up like a Christmas tree! North America is also pretty light. On the other hand, South America is quite dark.

I also find it interesting that Asia, which is known for their ability to work hard and focus, seem to be quite average. Perhaps, this is where capitalism excels.

Conscientious people are typically correlated with success, as they’re able to complete their work thoroughly. With this hard work, they’re able to suceed more in capitalistic countries.

cheerio!!! @ref(fig:opn world map) wahahaa

(#fig:agr world map)Diamond sadasds

Higher scores are correlated with agreeableness, lower scores are correlated egocentrism.

Table 10: Most Agreeable
region agrScores
Papua New Guinea 11.04167
Rwanda 10.56250
Cameroon 10.45455
St. Lucia 10.42857
Cuba 10.20833
Tanzania 10.17442
Table 10: Least Agreeable
region agrScores
Madagascar 1.500000
Åland Islands 1.533333
Bhutan 3.428571
Poland 3.818162
Cape Verde 3.909091
Belarus 3.927711

Agreeableness looks pretty similar to the contenciousness graph. It’s difficult to not find the most agreeable countries the most egotistical, as they must think they’re always so agreeable! However, you can just say that these countries value politeness highly.

It’s also interesting to note that Asian countries typically are very resepctful of their elders, and bend to their will. This idea is not really represented within this graph.

(#fig:opn world map)Diamond Prices

Higher scores are correlated with inquisition, lower scores are correlated indifference.

Table 11: Most Inquisitive
region opnScores
Madagascar 12.50000
Cuba 11.37500
Seychelles 11.36364
St. Lucia 11.04762
Armenia 10.91743
Germany 10.89598
Table 11: Least Inquisitve
region opnScores
Macao SAR China 3.506623
Bhutan 3.642857
Cambodia 3.971429
Malaysia 4.221204
Nepal 4.783489
Gambia 5.300000

The southern hemisphere seems to be more open compared to the Northern hemisphere, with Europe being the exception.

Are All Questions Created Equal?

We can also analyze the questions themselves. A funky little thing that this quiz did, was record how many milliseconds each respondent spent on each question. That seems like a fun thing to look at….

Thus, I present to you: General time spent on each question!

This is a good visual to compare questions to each other, especially questions in the same category.

For your reference:

For those unaware, this is a box plot17. The white box symbolizes the interquartile range, with the lower half of the box showing the bottom 25%, while the top half of the box shows the top 25%. The line in the center is the median of the question. It’s really good for visualizing the spread of data (which seems to range quite a bit). However, I’ve skewed the data by cutting off any values above 20 seconds18 and only took a random sample of 500 response times for each question19.

However, I want to be more precise with these loading times, so I’ve specifically pulled the questions that take the longest and shortest times to complete.

Table 12: Questions That Took the Longest
Category Question Time in Seconds
OPN10_E I shirk my duties. 14.58576
EXT1_E I leave my belongings around. 13.19256
CSN8_E I am relaxed most of the time. 8.54769
EXT3_E I feel little concern for others. 7.27583
CSN10_E I don’t like to draw attention to myself. 7.15241
Table 12: Questions That Took the Shortest
Category Question Time in Seconds
AGR6_E I use difficult words. 3.69086
CSN7_E I often feel blue. 3.53947
OPN8_E I have excellent ideas. 3.50618
EXT6_E I am full of ideas. 3.49672
EST9_E I have a rich vocabulary. 3.44563

I’ve taken the liberty of removing EXT_1 (the first question on the quiz), which had an average score of 87 seconds. This is likely because people people were getting accustomed to the quiz, had loading time issues, or started the quiz, then immediately forgot about it.

“I shirk my duties” took the longest, likely because ‘shirk’ is an uncommon word and people wanted to search up the definition, which easily could’ve taken an extra 10 seconds. As for the other questions, they’re all relatively long sentences and have more nuance. They’re all very situational, as people are rarely “always relaxed” or “never relaxed”, and it takes time to think whether you’re relax a MAJOURITY of the time. Same thing for little concern for others - there are tons of people you care about, but also, tons of people you don’t. So, it’s a bit tricky to answer those.

On the other hand, the questions that took the least amount of time are short and straightforward, and are obvious to judge yourself on. You either read a dictionary for fun to seem smart, or you don’t. I do find it interesting that it’s difficult for people to determine whether they’re ‘relaxed’ rather than ‘blue’. Likely because you conciously pay attention to when you’re sad, but not when you’re relaxed? You can also see that these questions are the ones that are asked later (e.g. AGR_9 is part of the 9th out of 10 rounds of questions, meaning that it’ll be really close to the ending of the quiz). Anticipation for results may have caused them to rush through the later questions.

Another interesting thing to note is the distrubtion of answers for each question. You may expected that each question has a distribution similar to standard deviation. However… that’s actually not the case! Many questions tend to have a distribution like so:

There are four major types of distribution seen in the data:

  1. Logarithmic (First Row)

The columns progressively increase or decrease. I think these graphs are the most “trustworthy”, as you’d only put 1 or 5 (the extremes) if you were incredibly confident in your answer.20 Not only that, but these questions aren’t really ‘shameful’ to admit, like “I get stressed out easily”, which allows people to be honest and pick extremes. Questions also tend to be less ‘situation’ and more ‘specific’, where you can very clearly visualize what you’d be doing in that situation, rather than responding “Oh… sometimes I am, sometimes I’m not!” (E.g. “I am quiet” likely wouldn’t follow this trend, but “I am quiet around strangers” probably does, because it helps narrow down the situation. You also don’t really change your behavior around different strangers, you usually are pretty constant with your behavior.)

Some other examples include:

If you’re wondering which side they skew on…. just trust your gut on it :)

  1. Skewed (Second Row)

i feel like these are best associated with questions where self-bias is most prevalent, as you want to make yourself as something you’re not (to make yourself feel better). These questions are also very situational; Sometimes I do this, sometimes I do. That’s why people tend to move towards the middle. This is the most common distribution type.

Examples include:

  1. “Normal” Distribution (Third Row, Left)

I’m lying to you - This graph isn’t normal distribution. I’m just calling it normal distribution because the answer 3 (neutral) is the most common answer. Quite frankly, it just means that people are either confused, or they don’t really have a large opinion on it, so they’re almost forced to choose 3. These questions seem to be the most ‘observable/objective’ of the bunch. Personally, I try to make a habit on avoiding clicking 3 no matter what (I’m not sure if others are the same), but it’s still interesting to see. I feel like these things are not things to be ‘proud’ of or dislike about yourself, nor would you mention it unless prompted, which is likely why it’s associated with the extrovertism questions.

Examples Include:

  1. Relatively Random (Third Row, Right)

So these are the ones that don’t follow a trend. Well, what happens is that 1 and 5 are similar in height and have about 150k responses, while 3, 4, 5 are also similar in height, with about 250k responses. It’s the kinds of questions that go “Yea… I’m definitely not SUPER ___, but it happens from time to time… I’m not sure how I would compare with other people though… so 2, 3, or 4 sound about right.”

Examples Include:


  1. Recall how introverted questions are negatively keyed and subtracted from your total.↩︎

  2. The average values will actually shift every time I update the website (on RStudio!), as the function ‘slice_sample’ will grab the average of 100 randomly selected responses, resulting in a unique average every time!↩︎

  3. https://www.wbur.org/hereandnow/2022/07/13/stress-survey-gallup↩︎

  4. https://www.voanews.com/a/why-people-worldwide-are-unhappier-more-stressed-than-ever-/6658784.html↩︎

  5. If someone told you, “Yea, you’re just a bit egocentric… no offense”, would you be happy about it?↩︎

  6. This was the only site that had theoretical values. I don’t know where they got their percentages from, and there was also no data on certain combinations. It should also be noted that this site does not use ‘X’ as a possible result. E.g. XLUEI (or any combination with an ‘X’) is not considered. So this source can not be completely trusted. It should also be noted that SimilarMinds separates the theoretical values by female and male. Since this data set does not have this distinction, I used the average of the male and female theoretical values to get my average number.↩︎

  7. Extroverted, stable, organized, agreeable, and inquisitive are all attributes that allow people to thrive, as they will tend to have larger social circles, better intrapersonal relationships and private lives, and the ability to study and work hard to get to positions they want academically and corporately.↩︎

  8. If you have more ideas, I’d love to hear them! Reach out :)↩︎

  9. There’s actually 3794 people who got XXXXX in this data set↩︎

  10. ‘Country codes’ are kinda misleading. There are ~195 countries, and ISO has 249 different codes. This is because the ISO contains subdivisions of countries, e.g. Caymen Islands (UK) and Christmas Island (Australia)↩︎

  11. https://www.searchenginejournal.com/ranking-factors/physical-proximity-to-searcher↩︎

  12. I couldn’t find any location data on the website itself↩︎

  13. As a Canadian, it’s actually the third search result!↩︎

  14. e.g. the 996 schedule of working from 9am to 9pm, 6 days a week↩︎

  15. Youth in China are adopting the philosophy of ‘lying down’ and giving up, due to the bad job market after graduation. They often feel let down by their society, as they’ve always been taught that studying hard and getting into a good university will lead to a good life. Yet, when they graduate, they struggle to find jobs and keep themselves afloat.↩︎

  16. E.g. To get into university, students take the Gaokao, a two-day standardized test that determines their entire future.↩︎

  17. I actually forgot this type of graph existed, until I was randomly scrolling through the ggplot2 library of different graph types!↩︎

  18. as it’s quite uncommon and makes plotting the graph difficult↩︎

  19. 500 is enough to show the general trend, and utilizing more only makes graphs take longer to load.↩︎

  20. If you ask people to choose a number between 1 and 5, they tend to pick 2, 3, or 4, rather than 1 or 5.↩︎

  21. This one is almost inverted, where 2 and 4 are the most common responses, followed by 1 and 5, then 3.↩︎